Snowdrop Scales Merchant Data Enrichment with Google Cloud
Provider of transaction enrichment solutions for banks and payment providers Snowdrop Solutions has significantly expanded its merchant reconciliation capabilities through a strategic migration to Google Cloud.
The company's Merchant Reconciliation System (MRS) API, which clarifies complex transaction data for financial institutions, now processes 1.47 billion transactions daily, up from 20 million before the migration.
Founded in 2013, Snowdrop specialises in enriching transactional data to improve transparency between financial institutions and their customers.
The company's technology addresses the challenge of deciphering confusing bank statement entries, which often result from the complex network of point-of-sale servers, payment processors and varying merchant names involved in each transaction.
Geospatial data boosts merchant recognition
Snowdrop's use of the Google Maps Platform, particularly the Google Places API, has been crucial in expanding its merchant database. The Places API provides localised merchant information, which Snowdrop combines with manually scraped website data to create more accurate transaction records.
Daniel Ritchie, Product Director at Snowdrop, explains the impact: “With Google Maps Platform geolocation data, we've increased the number of small merchants we can recognise within our system by hundreds of thousands, resulting in a 10-15% increase in our merchant-to-transaction match rate."
Cloud migration enables global scalability
The company's migration to Google Cloud was driven by the need for improved platform performance, stability and global expansion capabilities.
Snowdrop now utilises Cloud Storage for unstructured data and BigQuery as its data warehouse, enabling rapid deployment in new regions.
“We've scaled significantly without spending significantly more because our infrastructure is flexible and efficient in how it charges us only for resources used. This means we can trickle down our cost-efficiency to our users by producing high-value solutions that are more affordable for them,” says Daniel Acosta, Head of Technology at Snowdrop.
The migration has reduced the time required to ingest new client data from 90 days to two weeks, with a 40% improvement in accuracy. Cloud Service Mesh facilitates faster API deployment across regions, while Google Kubernetes Engine provides automated workload management and cost-efficient resource scaling.
AI-assisted merchant reconciliation
Snowdrop has integrated Vertex AI with BigQuery to automate aspects of its merchant reconciliation process. This AI-assisted approach has enabled the company to expand its merchant database by a factor of 100,500 compared to pre-migration levels.
Daniel Ritchie adds: “We have 100,500 times more merchants in our system compared to before our migration, and team members use Vertex AI to train our system to recognise and match these merchants with their respective transactions.
“The result is much more information and accuracy for our clients’ end customers, something that we wouldn’t be able to provide at this scale without automation.”
The company plans to further enhance its capabilities using AlloyDB and Gemini for Google Cloud. These technologies will enable more efficient data management and improved processing of multilingual merchant information.
Acosta highlights the benefits of the Google Cloud partnership: “In a couple of months, two brand new engineers will be certified thanks to the Google Cloud Partner Advantage Program.
“Collaborating with Google Cloud is great for morale: We're always learning, accessing early demos of products and features, and better placed to continue innovating and developing our solution.”
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